gcp-cloud-sql
Provision and manage Cloud SQL instances on Google Cloud for MySQL, PostgreSQL, and SQL Server. Configure high availability, read replicas, automated backups, IAM database authentication, the Cloud SQL Auth Proxy, and Terraform deployments. Use for managed relational databases on GCP.
What this skill does
# GCP Cloud SQL
## Overview
Cloud SQL is Google Cloud's managed relational database service for MySQL, PostgreSQL, and SQL Server. It handles patches, upgrades, replication, automated backups, point-in-time recovery, and HA failover so applications focus on schema and queries instead of database administration.
## Instructions
### Core Concepts
- **Instance** — a managed VM running MySQL/Postgres/SQL Server with attached storage
- **High Availability (HA)** — synchronous replica in another zone with automatic failover
- **Read replica** — async read-only copy for scaling reads or cross-region DR
- **Cloud SQL Auth Proxy** — local sidecar that handles IAM auth, TLS, and connection routing
- **Private IP** — instance reachable only via VPC peering, never the public internet
- **Point-in-time recovery (PITR)** — restore to any second within the retention window using binary logs
### Prerequisites
```bash
gcloud services enable sqladmin.googleapis.com servicenetworking.googleapis.com
# One-time: reserve a private range for VPC peering (for private IP instances)
gcloud compute addresses create google-managed-services-default \
--global --purpose=VPC_PEERING --prefix-length=16 \
--network=default
gcloud services vpc-peerings connect \
--service=servicenetworking.googleapis.com \
--ranges=google-managed-services-default --network=default
```
### Creating a PostgreSQL Instance with HA
```bash
gcloud sql instances create orders-db \
--database-version=POSTGRES_15 \
--tier=db-custom-2-7680 \
--region=us-central1 \
--availability-type=REGIONAL \
--network=default \
--no-assign-ip \
--backup-start-time=02:00 \
--enable-point-in-time-recovery \
--retained-backups-count=14 \
--database-flags=cloudsql.iam_authentication=on,log_min_duration_statement=500
```
```bash
# Set the postgres password (or skip and use IAM auth exclusively)
gcloud sql users set-password postgres \
--instance=orders-db \
--password="$(openssl rand -base64 24)"
# Create application database and user
gcloud sql databases create orders --instance=orders-db
gcloud sql users create app_user --instance=orders-db --password="$(openssl rand -base64 24)"
```
### Creating a MySQL Instance
```bash
gcloud sql instances create analytics-db \
--database-version=MYSQL_8_0 \
--tier=db-n1-standard-2 \
--region=us-central1 \
--storage-type=SSD \
--storage-size=100 \
--storage-auto-increase \
--backup-start-time=03:00 \
--enable-bin-log
```
### Read Replicas
```bash
# Read replica in the same region (scale reads)
gcloud sql instances create orders-db-replica \
--master-instance-name=orders-db \
--region=us-central1 \
--tier=db-custom-2-7680
```
```bash
# Cross-region replica (DR + low-latency reads in another region)
gcloud sql instances create orders-db-eu \
--master-instance-name=orders-db \
--region=europe-west1 \
--tier=db-custom-2-7680
```
```bash
# Promote a replica to a standalone primary (DR failover)
gcloud sql instances promote-replica orders-db-eu
```
### Connecting via Cloud SQL Auth Proxy
```bash
# Get the connection name
gcloud sql instances describe orders-db --format="value(connectionName)"
# Returns: my-project:us-central1:orders-db
# Run the proxy locally
./cloud-sql-proxy --port 5432 my-project:us-central1:orders-db
# In another terminal:
psql "host=127.0.0.1 port=5432 user=app_user dbname=orders"
```
```yaml
# Cloud Run sidecar pattern (Cloud Run handles the proxy automatically with --add-cloudsql-instances)
# For GKE, deploy the proxy as a sidecar in the same pod:
apiVersion: apps/v1
kind: Deployment
metadata:
name: api
spec:
template:
spec:
serviceAccountName: api-sa # bound to a GSA with roles/cloudsql.client
containers:
- name: api
image: gcr.io/my-project/api:latest
env:
- name: DATABASE_URL
value: "postgresql://[email protected]:5432/orders"
- name: cloud-sql-proxy
image: gcr.io/cloud-sql-connectors/cloud-sql-proxy:2.11.0
args:
- "--auto-iam-authn"
- "--private-ip"
- "my-project:us-central1:orders-db"
securityContext:
runAsNonRoot: true
```
### IAM Database Authentication
```bash
# Add a service account as a Postgres database user
gcloud sql users create [email protected] \
--instance=orders-db \
--type=cloud_iam_service_account
```
```sql
-- Grant database privileges (run as postgres superuser)
GRANT CONNECT ON DATABASE orders TO "[email protected]";
GRANT USAGE ON SCHEMA public TO "[email protected]";
GRANT SELECT, INSERT, UPDATE ON ALL TABLES IN SCHEMA public TO "[email protected]";
```
The application uses no static password — the proxy fetches a short-lived OAuth token from the metadata server and passes it as the database password.
### Backups and Point-in-Time Recovery
```bash
# Manual on-demand backup before risky migration
gcloud sql backups create --instance=orders-db --description="pre-v2-migration"
```
```bash
# Restore the database to a specific point in time (requires PITR enabled)
gcloud sql instances clone orders-db orders-db-recovery \
--point-in-time='2026-04-15T14:30:00Z'
```
### Terraform
```hcl
resource "google_sql_database_instance" "orders" {
name = "orders-db"
database_version = "POSTGRES_15"
region = "us-central1"
deletion_protection = true
settings {
tier = "db-custom-2-7680"
availability_type = "REGIONAL"
ip_configuration {
ipv4_enabled = false
private_network = data.google_compute_network.default.id
}
backup_configuration {
enabled = true
point_in_time_recovery_enabled = true
start_time = "02:00"
backup_retention_settings {
retained_backups = 14
}
}
database_flags {
name = "cloudsql.iam_authentication"
value = "on"
}
}
}
resource "google_sql_user" "app_sa" {
name = "app-sa@${var.project_id}.iam"
instance = google_sql_database_instance.orders.name
type = "CLOUD_IAM_SERVICE_ACCOUNT"
}
```
## Examples
### Example 1 — Migrate a self-hosted Postgres to Cloud SQL
User wants to move a 200 GB Postgres database to Cloud SQL with minimal downtime. Create a target instance with `--availability-type=REGIONAL` and PITR enabled, use Database Migration Service to perform a continuous logical replication from the source, run validation queries, then promote the destination during a short cutover window. Hand the user the new connection string via the Auth Proxy and a Terraform module for the instance.
### Example 2 — Add cross-region read replica for EU users
User reports high read latency from European users. Create a read replica in `europe-west1` with the same tier as primary, point the EU app instances at the replica's connection name through their Auth Proxy sidecars, and verify replication lag stays under 5 seconds via `gcloud sql operations` and Cloud Monitoring metrics.
## Guidelines
- Use **private IP only** in production — never expose Cloud SQL on a public IP
- Always set `availability-type=REGIONAL` for production workloads
- Enable PITR (`--enable-point-in-time-recovery`) — it's cheap insurance against accidental writes
- Prefer **IAM database authentication** over passwords — works for service accounts and human users
- Run the Cloud SQL Auth Proxy as a sidecar (Cloud Run, GKE) rather than embedding TLS logic in the app
- Pin database flags via Terraform so they survive instance recreation
- For schema migrations, take an on-demand backup first
- Monitor `cloudsql.googleapis.com/database/cpu/utilization` and connection count — alert at 80%
- Read replicas are async — never write to them and assume eventual consistency for reads from them
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.